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Bibliography

Major publications by the team in recent years
  • 1R. Cofré, B. Cessac.

    Dynamics and spike trains statistics in conductance-based integrate-and-fire neural networks with chemical and electric synapses, in: Chaos, Solitons & Fractals, 2013, vol. 50, no 13, 3 p.
  • 2R. Cofré, B. Cessac.

    Exact computation of the maximum-entropy potential of spiking neural-network models, in: Phys. Rev. E, 2014, vol. 89, no 052117.
  • 3M.-J. Escobar, G. S. Masson, T. Viéville, P. Kornprobst.

    Action Recognition Using a Bio-Inspired Feedforward Spiking Network, in: International Journal of Computer Vision, 2009, vol. 82, no 3, 284 p.
  • 4O. Faugeras, J. Touboul, B. Cessac.

    A constructive mean field analysis of multi population neural networks with random synaptic weights and stochastic inputs, in: Frontiers in Computational Neuroscience, 2009, vol. 3, no 1. [ DOI : 10.3389/neuro.10.001.2010 ]

    http://arxiv.org/abs/0808.1113
  • 5T. Masquelier, G. Portelli, P. Kornprobst.

    Microsaccades enable efficient synchrony-based coding in the retina: a simulation study, in: Scientific Reports, April 2016, vol. 6, 24086. [ DOI : 10.1038/srep24086 ]

    http://hal.upmc.fr/hal-01301838
  • 6D. Matzakos-Karvouniari, L. Gil, E. Orendorff, O. Marre, S. Picaud, B. Cessac.

    A biophysical model explains the spontaneous bursting behavior in the developing retina, in: Scientific Reports, December 2019, vol. 9, no 1, pp. 1-23. [ DOI : 10.1038/s41598-018-38299-4 ]

    https://hal.sorbonne-universite.fr/hal-02045700
  • 7N. V. K. Medathati, H. Neumann, G. S. Masson, P. Kornprobst.

    Bio-Inspired Computer Vision: Towards a Synergistic Approach of Artificial and Biological Vision, in: Computer Vision and Image Understanding (CVIU), April 2016. [ DOI : 10.1016/j.cviu.2016.04.009 ]

    https://hal.inria.fr/hal-01316103
  • 8J. Naudé, B. Cessac, H. Berry, B. Delord.

    Effects of Cellular Homeostatic Intrinsic Plasticity on Dynamical and Computational Properties of Biological Recurrent Neural Networks, in: Journal of Neuroscience, 2013, vol. 33, no 38, pp. 15032-15043. [ DOI : 10.1523/JNEUROSCI.0870-13.2013 ]

    https://hal.inria.fr/hal-00844218
  • 9J. Rankin, A. I. Meso, G. S. Masson, O. Faugeras, P. Kornprobst.

    Bifurcation Study of a Neural Fields Competition Model with an Application to Perceptual Switching in Motion Integration, in: Journal of Computational Neuroscience, 2014, vol. 36, no 2, pp. 193–213.
  • 10A. Wohrer, P. Kornprobst.

    Virtual Retina : A biological retina model and simulator, with contrast gain control, in: Journal of Computational Neuroscience, 2009, vol. 26, no 2, 219 p, DOI 10.1007/s10827-008-0108-4.
Publications of the year

Doctoral Dissertations and Habilitation Theses

  • 11S. Souihel.

    Generic and specific computational principles for visual anticipation of motion trajectories, Université Nice Côte d'Azur ; EDSTIC, December 2019.

    https://hal.inria.fr/tel-02414632

Articles in International Peer-Reviewed Journals

  • 12M. Carlu, O. Chehab, L. Dalla Porta, D. Depannemaecker, C. Héricé, M. Jedynak, E. Köksal Ersöz, P. Muratore, S. Souihel, C. Capone, Y. Zerlaut, A. Destexhe, M. Di Volo.

    A mean-field approach to the dynamics of networks of complex neurons, from nonlinear Integrate-and-Fire to Hodgkin-Huxley models, in: Journal of Neurophysiology, December 2019, forthcoming. [ DOI : 10.1152/jn.00399.2019 ]

    https://hal.inria.fr/hal-02414751
  • 13B. Cessac.

    Linear response in neuronal networks: from neurons dynamics to collective response, in: Chaos, October 2019, vol. 29, no 103105. [ DOI : 10.1063/1.5111803 ]

    https://hal.inria.fr/hal-02280089
  • 14D. Matzakos-Karvouniari, L. Gil, E. Orendorff, O. Marre, S. Picaud, B. Cessac.

    A biophysical model explains the spontaneous bursting behavior in the developing retina, in: Scientific Reports, December 2019, vol. 9, no 1, pp. 1-23. [ DOI : 10.1038/s41598-018-38299-4 ]

    https://hal.sorbonne-universite.fr/hal-02045700
  • 15N. Stolowy, A. Calabrese, L. Sauvan, C. Aguilar, T. François, N. Gala, F. Matonti, E. Castet.

    The influence of word frequency on word reading speed when individuals with macular diseases read text, in: Vision Research, February 2019, vol. 155, pp. 1-10. [ DOI : 10.1016/j.visres.2018.12.002 ]

    https://hal.archives-ouvertes.fr/hal-02360849

Invited Conferences

  • 16B. Cessac, D. Matzakos-Karvouniari, L. Gil.

    Modelling spontaneous propagating waves in the early retina, in: Waves Côte d'azur, Nice, France, June 2019.

    https://hal.inria.fr/hal-02268281
  • 17B. Cessac, S. Souihel.

    Motion anticipation in the retina, in: NeuroSTIC 2019 - 7e édition des journées NeuroSTIC, Sophia-Antipolis, France, October 2019.

    https://hal.inria.fr/hal-02316888
  • 18B. Cessac, S. Souihel, M. Di Volo, F. Chavane, A. Destexhe, S. Chemla, O. Marre.

    Anticipation in the retina and the primary visual cortex : towards an integrated retino-cortical model for motion processing, in: Workshop on visuo motor integration, Paris, France, June 2019.

    https://hal.inria.fr/hal-02150600
  • 19E. Kartsaki, B. Cessac, G. Hilgen, E. Sernagor.

    Probing retinal function with a multi-layered simulator, in: The Rank Prize Funds - Symposium on The retinal processing of natural signals, Grasmere, United Kingdom, June 2019.

    https://hal.archives-ouvertes.fr/hal-02389076

International Conferences with Proceedings

  • 20S. Souihel, B. Cessac.

    Anticipation in the retina and the primary visual cortex : towards an integrated retino-cortical model for motion processing, in: ICMNS 2019 - The 5th International Conference on Mathematical NeuroScience, Copenhague, Denmark, June 2019.

    https://hal.inria.fr/hal-02167737
  • 21S. Souihel, B. Cessac, M. D. Volo, A. Destexhe, F. Chavane, S. Chemla, O. Marre.

    Anticipation in the retina and the primary visual cortex : towards an integrated retino-cortical model for motion processing, in: Waves Côte d'Azur, Nice, France, June 2019.

    https://hal.inria.fr/hal-02172010
  • 22S. Souihel, B. Cessac, M. D. Volo, A. Destexhe, F. Chavane, S. Chemla, O. Marre.

    Anticipation in the retina and the primary visual cortex : towards an integrated retino-cortical model for motion processing, in: NeuroMod 2019 - First meeting of the NeuroMod Institute, Fréjus, France, July 2019.

    https://hal.inria.fr/hal-02172016

National Conferences with Proceedings

  • 23B. Cessac, M. Mantegazza.

    Modelling of physiological and pathological states in neuroscience: exchanges among theoreticians and experimentalists, in: NeuroMod 2019 - First meeting of the NeuroMod Institute, Fréjus, France, July 2019.

    https://hal.inria.fr/hal-02171428

Conferences without Proceedings

  • 24E. Kartsaki, B. Cessac, G. Hilgen, E. Sernagor.

    Probing retinal function with a multi-layered simulator, in: NeuroMod 2019 - First meeting of the NeuroMod Institute, Fréjus, France, July 2019.

    https://hal.archives-ouvertes.fr/hal-02389086
  • 25D. Karvouniari, L. Gil, O. Marre, S. Picaud, B. Cessac.

    Multi scale dynamics in retinal waves, in: LACONEU 2019 - 5th Latin American Summer School in Computational Neuroscience - Workshop Large Scale Network Dynamics, Valparaiso, Chile, January 2019.

    https://hal.archives-ouvertes.fr/hal-01986989

Internal Reports

  • 26H.-Y. Wu, A. Calabrese, P. Kornprobst.

    Towards Accessible News Reading Design in Virtual Reality for Low Vision, UCA ; Inria, October 2019, no RR-9298, 20 p.

    https://hal.inria.fr/hal-02321739
  • 27H.-Y. Wu, P. Kornprobst.

    Multilayered Analysis of Newspaper Structure and Design, UCA, Inria, July 2019, no RR-9281.

    https://hal.inria.fr/hal-02177784

Other Publications

References in notes
  • 36W. I. Al-Atabany, M. A. Memon, S. M. Downes, P. A. Degenaar.

    Designing and testing scene enhancement algorithms for patients with retina degenerative disorders, in: Biomedical engineering online, 2010, vol. 9, no 1, 27 p.
  • 37W. I. Al-Atabany, T. Tong, P. A. Degenaar.

    Improved content aware scene retargeting for retinitis pigmentosa patients, in: Biomedical engineering online, 2010, vol. 9, no 1.
  • 38H. Alhéritière, F. Cloppet, C. Kurtz, J.-M. Ogier, N. Vincent.

    A document straight line based segmentation for complex layout extraction, in: Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017.
  • 39F. M. Atay, S. Banisch, P. Blanchard, B. Cessac, E. Olbrich.

    Perspectives on Multi-Level Dynamics, in: The interdisciplinary journal of Discontinuity, Nonlinearity, and Complexity, 2016, vol. 5, pp. 313 - 339. [ DOI : 10.5890/DNC.2016.09.009 ]

    https://hal.inria.fr/hal-01387733
  • 40M. Auvray, E. Myin.

    Perception With Compensatory Devices: From Sensory Substitution to Sensorimotor Extension, in: Cognitive Science, 2009, vol. 33, no 6, pp. 1036–1058.

    http://dx.doi.org/10.1111/j.1551-6709.2009.01040.x
  • 41S. Avidan, A. Shamir.

    Seam Carving for Content-aware Image Resizing, in: ACM Trans. Graph., July 2007, vol. 26, no 3.

    http://doi.acm.org/10.1145/1276377.1276390
  • 42B. Cessac, R. Cofre.

    Linear response for spiking neuronal networks with unbounded memory, October 2018, https://arxiv.org/abs/1704.05344 - working paper or preprint.

    https://hal.inria.fr/hal-01895095
  • 43B. Cessac, R. Cofré.

    Spike train statistics and Gibbs distributions, in: Journal of Physiology-Paris, November 2013, vol. 107, no 5, pp. 360-368, Special issue: Neural Coding and Natural Image Statistics.

    http://hal.inria.fr/hal-00850155
  • 44C. Clausner, A. Antonacopoulos, S. Pletschacher.

    ICDAR2017Competition on Recognition of Documents with Complex Layouts–RDCL2017, in: Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition, 2017.
  • 45Á. Csapó, G. Wersényi, H. Nagy, T. Stockman.

    A survey of assistive technologies and applications for blind users on mobile platforms: a review and foundation for research, in: Journal on Multimodal User Interfaces, 2015, vol. 9, no 4, pp. 275–286.

    http://dx.doi.org/10.1007/s12193-015-0182-7
  • 46M. Djilas, B. Kolomiets, L. Cadetti, H. Lorach, R. Caplette, S. Ieng, A. Rebsam, J. A. Sahel, R. Benosman, S. Picaud.

    Pharmacologically Induced Wave-Like Activity in the Adult Retina, in: ARVO Annual Meeting Abstract, March 2012.
  • 47S. I. Firth, C.-T. Wang, M. B. Feller.

    Retinal waves: mechanisms and function in visual system development, in: Cell Calcium, 2005, vol. 37, no 5, pp. 425 - 432, Calcium in the function of the nervous system: New implications. [ DOI : 10.1016/j.ceca.2005.01.010 ]

    http://www.sciencedirect.com/science/article/pii/S0143416005000278
  • 48K. J. Ford, M. B. Feller.

    Assembly and disassembly of a retinal cholinergic network, in: Visual Neuroscience, 2012, vol. 29, pp. 61–71. [ DOI : 10.1017/S0952523811000216 ]

    http://journals.cambridge.org/article_S0952523811000216
  • 49B. Froissard.

    Assistance visuelle des malvoyants par traitement d'images adaptatif, Université de Saint-Etienne, February 2014.
  • 50B. Froissard, H. Konik, E. Dinet.

    Digital content devices and augmented reality for assisting low vision people, in: Visually Impaired: Assistive Technologies, Challenges and Coping Strategies, Nova Science Publishers, December 2015.

    https://hal-ujm.archives-ouvertes.fr/ujm-01222251
  • 51E. Ganmor, R. Segev, E. Schneidman.

    Sparse low-order interaction network underlies a highly correlated and learnable neural population code, in: PNAS, 2011, vol. 108, no 23, pp. 9679-9684.
  • 52E. Ganmor, R. Segev, E. Schneidman.

    The architecture of functional interaction networks in the retina, in: The journal of neuroscience, 2011, vol. 31, no 8, pp. 3044-3054.
  • 53D. Gautier, C. Gautier.

    Design, Typography, etc. A Handbook, Niggli, 2018.
  • 54M. Hersh, M. Johnson.

    Assistive Technology for Visually Impaired and Blind People, Springer, London, 2010, pp. 575-576.
  • 55E. Jaynes.

    Information theory and statistical mechanics, in: Phys. Rev., 1957, vol. 106, 620 p.
  • 56H. Moshtael, T. Aslam, I. Underwood, B. Dhillon.

    High Tech Aids Low Vision: A Review of Image Processing for the Visually Impaired, in: Translational vision science & technology (TVST), 2015, vol. 4, no 4.
  • 57E. Schneidman, M. Berry, R. Segev, W. Bialek.

    Weak pairwise correlations imply strongly correlated network states in a neural population, in: Nature, 2006, vol. 440, no 7087, pp. 1007–1012.
  • 58E. Sernagor, M. Hennig.

    1, in: Retinal Waves: Underlying Cellular Mechanisms and Theoretical Considerations, J. Rubenstein, P. Rakic (editors), Elsevier, 2012.
  • 59J. Shlens, G. Field, J. Gauthier, M. Grivich, D. Petrusca, A. Sher, A. Litke, E. Chichilnisky.

    The Structure of Multi-Neuron Firing Patterns in Primate Retina, in: Journal of Neuroscience, 2006, vol. 26, no 32, 8254 p.
  • 60The Lasker/IRRF Initiative for Innovation in Vision Science.

    Chapter 7- Restoring Vision to the Blind: Advancements in Vision Aids for the Visually Impaired, in: Translational Vision Science & Technology, 2014, vol. 3, no 7, 9 p.

    http://dx.doi.org/10.1167/tvst.3.7.9
  • 61G. Tkacik, O. Marre, T. Mora, D. Amodei, M. Berry, W. Bialek.

    The simplest maximum entropy model for collective behavior in a neural network, in: J Stat Mech, 2013, P03011 p.
  • 62J.-C. Vasquez, A. Palacios, O. Marre, M. J. Berry, B. Cessac.

    Gibbs distribution analysis of temporal correlations structure in retina ganglion cells, in: J. Physiol. Paris, May 2012, vol. 106, no 3-4, pp. 120-127.

    http://arxiv.org/abs/1112.2464
  • 63R. O. L. Wong, M. Meister, C. J. Shatz.

    Transient Period of Correlated Bursting Activity During Development of the Mammalian Retina, in: Neuron, November 1993, vol. 11, no 5, pp. 923–938.
  • 64H. Xu, T. Burbridge, M. Ye, X. Ge, Z. Zhou, M. Crair.

    Retinal Wave Patterns Are Governed by Mutual Excitation among Starburst Amacrine Cells and Drive the Refinement and Maintenance of Visual Circuits, in: The Journal of Neuroscience, 2016, vol. 36, no 13, pp. 3871-3886.


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